Textbook in PDF format

Computational intelligence (CI) in concrete technology has not yet been fully explored worldwide because of some limitations in data sets. This book discusses the selection and separation of data sets, performance evaluation parameters for different types of concrete and related materials, and sensitivity analysis related to various CI techniques. Fundamental concepts and essential analysis for CI techniques such as artificial neural network, fuzzy system, support vector machine, and how they work together for resolving real-life problems, are explained. The technical content included is beneficial for researchers as well as practicing engineers in the concrete and construction industry.
Usage of Computational Intelligence Techniques in Concrete Technology
Developing Random Forest Random Tree and Linear Regression Model to Predict Compressive Strength of Concrete Using Glass Fiber
Prediction of Compressive Strength at Elevated Temperatures Using Machine Learning Methods
Implementation of Machine Learning Approaches to Evaluate Flexural Strength of Concrete With Glass Fiber
A Comparative Study Using ANFIS and ANN for Determining the Compressive Strength of Concrete
Prediction of Concrete Mix Compressive Strength Using Waste Marble Powder: A Comparison of ANN, RF, RT, and LR models
Using GA to Predict the Compressive Strength of Concrete Containing Nano-Silica
Evaluation of Models by Soft Computing Techniques for the Prediction of Compressive Strength of Concrete Using Steel Fibre
Using Regression Model to Estimate the Splitting Tensile Strength for the Concrete With Basalt Fiber Reinforced Concrete
Prediction of Compressive Strength of Self-Compacting Concrete Containing Silica’s Using Soft Computing Techniques
Using Soft Computing Techniques to Predict the Values of Compressive Strength of Concrete with Basalt Fiber Reinforced Concrete
Soft Computing-Based Prediction of Compressive Strength of High Strength Concrete
Forecasting Compressive Strength of Concrete Containing Nano-Silica Using Particle Swarm Optimization Algorithm and Genetic Algorithm
Prediction of Ultrasonic Pulse Velocity of Concrete
Evaluation of ANN and Tree-Based Techniques for Predicting the Compressive Strength of Granite Powder Reinforced Concrete
Predicting Recycled Aggregates Compressive Strength in High-Performance Concrete Using Artificial Neural Networks
Compressive Strength Prediction and Analysis of Concrete Using Hybrid Artificial Neural Networks